01

Research & product definition

Is this a real problem—and is there enough of a market?

LionelDomain expertise · Product definition · Business strategy · Research · Testing

AI partnersChatGPT · Claude — market research · modeling · structuring · validation

Context

I already knew the domain from cutting and polishing opals. What I didn’t know was whether the problem was big enough to support a product.

Challenge

Turn expert judgment into something structured enough for a consumer experience and an AI grader, while testing whether realistic adoption and pricing could support a business.

Goal

Answer two questions: can this become a useful product, and is the niche still large enough to make building it worthwhile?

Starting with a problem I already understood

I documented the characteristics I already use when looking at a stone and turned that knowledge into explicit product requirements. AI helped me organize the information, challenge assumptions and validate the areas where I wanted additional research.

Testing the business case

I used AI for market research, competitor analysis, pricing exploration and realistic subscription modeling. I deliberately used conservative assumptions rather than a pitch-deck version of the opportunity. The conclusion was encouraging: the market is niche, but there is still enough demand to support a real business if the product earns trust and keeps operating costs under control.

Serious collectorNeeds evidence, control and enough detail to challenge the result.

Casual sellerNeeds speed, clarity and confidence without learning the entire taxonomy.

Product requirementsRange, confidence, evidence, corrections and guided capture.

02

UX architecture

Structure first. Style second.

LionelProduct strategy · IA · Flows · Interaction design · Review

AI partnersChatGPT · Claude Design — screen mapping · exploration · prototyping

Context

The idea was already bigger than “take a picture and get a price.” It needed onboarding, capture, grading, evidence, corrections, collection and account states.

Challenge

Make a complex grading and valuation process understandable to both a serious collector looking for evidence and a casual seller looking for confidence.

Goal

Resolve the information architecture and core flows before making visual design decisions.

Two users, two kinds of confidence

The serious collector needs evidence. The casual seller needs speed and confidence. Results therefore use ranges rather than one magic number, surface confidence instead of hiding it, and let users go deeper without forcing everyone through the same detail.

Capture became part of the UX

A useful grading pass depends on movement, lighting, multiple views and a physical size reference. The product guides capture instead of treating video as a generic upload step.

Guiding principles

1. Honesty over polish — “the honest eye.”Never claim more than we know.

2. Trust is earned by showing the evidence.Disclosed before charged. Never a fabricated count, never a hidden caveat.

03

Brand & design system

Turning a visual direction into a system that could move into code.

LionelCreative direction · Brand · Visual design · Design system · QA

AI partnersChatGPT · Claude Design — exploration · production · system documentation

Context

With the product structure working, I could focus on how Opalescent should look and feel.

Challenge

Opals are visually spectacular. The interface needed to feel credible without turning into rainbow gradients, gem-show decoration or generic AI styling.

Goal

Create a clear brand and standardize it into reusable rules that could carry directly from prototype to production.

The stone is the star

I explored multiple visual directions and kept coming back to the same principle: the interface should recede and let the opal provide the color.

Standardization was the next step

Once the direction was established, I formalized typography, color, spacing, states, confidence treatments and reusable components. Instead of handing off individually styled screens, I could hand off rules.

Quiet surfacesWarm neutrals keep attention on the stone.

Meaningful colorColor supports opal data and confidence—not decoration.

Reusable rulesTokens and components carried the prototype into production.

Current welcome screen — the design system carried into the closed-beta build.

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